• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.419-421
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• 2015

미래 NCW의 핵심은 전투상황에 대한 정보를 데이터 특성에 따라 얼마나 신속 정확하게 공유하느냐가 중요하다. 이를 위해 대한민국 육군은 다양한 개인병사부터 합참에 이르기까지 각종 상황인식과 지휘통제에 필요한 데이터를 수집, 종합, 타격하는 체계를 구축하고 있다. 하지만, 통신장비와 전장단말기가 분리되어 있음에 따라 운용상 많은 제한사항이 있다. 이를 극복하기 위해 통신장비와 전장단말기를 통합하는 형태의 통합형 단말기가 강구되고 있으며, 이는 개인병사체계 및 무인지상감시 센서 등에서 개념 연구가 되어지고 있다. 하지만, 가장 중요한 부분인 데이터 송수신에 대한 최적의 방안이 미정립되어 있음에 따라 본 연구에서는 전송지연시간 단축 및 재전송 알고리즘 개선 등을 통한 효율적인 전송방안을 제안하고, 이를 시험을 통해 검증함으로써 미래 통합형 전장단말기의 데이터 전송관련 설계 방향을 제시하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.945-948
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• 2015

본 연구는 비 정형 농산물 중 6년근 수삼의 자동 등급 분류하기 위한 선행연구로, 이를 위해 4방향에서 측정 가능케 하는 수삼 측정기를 제작하였으며, 측정된 수삼영상에서 뼈대와 몸통부분을 인식하기 위한 알고리즘을 고안하여 적용하였다. 적용 결과 6년 근 수삼에서 홍삼으로 만들어 졌을 때 가공 후 영상을 추정가능하다는 것을 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.271-273
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• 2021

본 논문은 이동노드의 클러스터링내에서 보다 효율적인클러스터링을 제공하고 유지하기위한 딥러닝의 선형회귀적 적응적 보정가중치에 따른 군집적 알고리즘을 제안한다. 대부분의 클러스터링 군집데이터를 처리함에 있어 상호관계에 따른 분류체계가 제공된다. 이러한 경우 이웃한 이동노드중 목적노드와는 연결가능성이 가장높은 이동노드를 클러스터내에서 중계노드로 선택해야 한다. 본 연구에서는 이러한 상황정보를 이해하고 동적이동노드간 속도와 방향속성정보간의 상관관계의 친밀도를 고려한 자율학습기반의 회귀적 모델에서 적응적 가중치에 따른 분류를 제시한다. 본 논문에서는 이러한 상황정보를 이해하고 클러스터링을 유지할 수 있는 자율학습기반의 적응적 가중치에 따른 딥러닝 모델을 제시 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.59-68
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• 1999

Recently, research and developmental direction of communication system is concurrent adopting voice data and face image in speaking to provide more higher recognition rate then in the case of only voice data. Therefore, we present a method of lipreading in speech image sequence by using the 3-D facial shape model. The method use a feature information of the face image such as the opening-level of lip, the movement of jaw, and the projection height of lip. At first, we adjust the 3-D face model to speeching face image sequence. Then, to get a feature information we compute variance quantity from adjusted 3-D shape model of image sequence and use the variance quality of the adjusted 3-D model as recognition parameters. We use the intensity inclination values which obtaining from the variance in 3-D feature points as the separation of recognition units from the sequential image. After then, we use discrete HMM algorithm at recognition process, depending on multiple observation sequence which considers the variance of 3-D feature point fully. As a result of recognition experiment with the 8 Korean vowels and 2 Korean consonants, we have about 80% of recognition rate for the plosives and vowels. We propose that usability with visual distinguishing factor that using feature vector because as a result of recognition experiment for recognition parameter with the 10 korean vowels, obtaining high recognition rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.427-439
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• 2006

The SBF (Simple Boundary Follower) is a boundary-following algorithm, and is used mainly for image recognition and presentation. The SBF is very popular because of its simplicity and efficiency in tracing the boundary of an object from an acquired binary image; however, it does have two drawbacks. First, the SBF cannot consistently process inner or inner-outer corners according to the follower's position and direction. Second, the SBF requires movement operations for the non-boundary pixels that are connected to boundary pixels. The MSBF (Modified Simple Boundary Follower) has a diagonal detour step for preventing inner-outer corner inconsistency, but is still inconsistent with inner-corners and still requires extra movement operations on non-boundary pixels. In this paper, we propose the ISBF (Improved Simple Boundary Follower), which solves the inconsistencies and reduces the extra operations. In addition, we have classified the tour maps by paths from a current boundary pixel to the next boundary pixel and have analyzed SBF, MSBF, and ISBF. We have determined that the ISBF has no inconsistency issues and reduces the overall number of operations.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Cartoon and Animation Studies
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• s.33
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• pp.403-423
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• 2013

Video images of emotional happiness or unhappiness, stress or emotional division of tranquility in the form of a tree is evaluated by weighting. Representative evaluation of the video image brightness contrast sensitivity ratings 1 car happy, unhappy or nervous, calm and refined with two car dependency, sensitivity to visual images are separated. Emotion Recognition of four compared to the numerical data is measured by brightness. OpenCV implementation through evaluation graph the stress intensity contrast, tranquility, happiness, unhappiness with changes in the value of four, separated by sensitivity to computing. Contrast sensitivity of computing the brightness according to the input value 'unhappy' to 'happy' or 'stress' to 'calm' the emotional changes are implemented. Emotion computing the regularity of the image to calculate the sensitivity localized computing system can be controlled according to the emotion of the contrast value of the brightness changes are implemented. The future direction of industry on the application of emotion recognition will play a positive role.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.157-163
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• 2014

User's sensitivity is recognized as a very important parameter for communication between company, government and personnel. Especially in many studies, researchers use voice tone, voice speed, facial expression, moving direction and speed of body, and gestures to recognize the sensitivity. Multiplex modality is more precise than single modality however it has limited recognition rate and overload of data processing according to multi-sensing also an excellent algorithm is needed to deduce the sensing value. That is as each modality has different concept and property, errors might be happened to convert the human sensibility to standard values. To deal with this matter, the sensibility expression modality is needed to be extracted using technologies like analyzing of relational network, understanding of context and digital filter from multiplex modality. In specific situation to recognize the sensibility if the priority modality and other surrounding modalities are processed to implicit values, a robust system can be composed in comparison to the consuming of computer resource. As a result of this paper, it is proposed how to assign the weight of multiplex modality using implicit data.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.562-570
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• 2013

Image of emotional pleasure or displeasure, tension or emotional division of tranquility in the form of a tree is evaluated by weighting. Image representative evaluation of the sensitivity of the brightness contrast ratings 1 car pleasure, displeasure or stress or emotional tranquility and two cars are separated by image segmentation. Emotion Recognition of four compared to the numerical data is measured by brightness. OpenCV implementation through evaluation graph the stress intensity contrast, tranquility, pleasure, displeasure, depending on changes in the value of the computing is divided into four emotional. Contrast sensitivity of computing the brightness depending on the value entered 'nuisance' to 'excellent' or 'stress' to 'calm' the emotional changes can give. Calculate the sensitivity of the image regularity of localized computing system can control the future direction of industry on the application of emotion recognition will play a positive role.